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We present for astrophysical use a multi-dimensional numerical code to solve the equations for ideal magnetohydrodynamics (MHD). It is based on an explicit finite difference method on an Eulerian grid, called the Total Variation Diminishing…

Astrophysics · Physics 2016-08-30 Dongsu Ryu , T. W. Jones , Adam Frank

In this paper, an energy-consistent finite difference scheme for the compressible hydrodynamic and magnetohydrodynamic (MHD) equations is introduced. For the compressible magnetohydrodynamics, an energy-consistent finite difference…

Computational Physics · Physics 2021-04-07 Haruhisa Iijima

We present a novel approach to compute three-dimensional Magnetohydrodynamic equilibria by parametrizing Fourier modes with artificial neural networks and compare it to equilibria computed by conventional solvers. The full nonlinear global…

Machine Learning · Computer Science 2026-03-31 Timo Thun , Andrea Merlo , Rory Conlin , Dario Panici , Daniel Böckenhoff

Magnetohydrodynamics (MHD) is invoked to address turbulent fluctuations in a variety of astrophysical systems. MHD turbulence in nature is often anisotropic and imbalanced, in that Alfvenic fluctuations moving in opposite directions along…

Astrophysics of Galaxies · Physics 2010-02-18 Jean C Perez , Stanislav Boldyrev

Due to the prevalence of magnetic fields in astrophysical environments, magnetohydrodynamic (MHD) simulation has become a basic tool for studying astrophysical fluid dynamics. To further advance the precision of MHD simulations, we have…

High Energy Astrophysical Phenomena · Physics 2023-08-09 Jeongbhin Seo , Dongsu Ryu

Most existing Heterogeneous Information Network (HIN) embedding methods focus on static environments while neglecting the evolving characteristic of realworld networks. Although several dynamic embedding methods have been proposed, they are…

Social and Information Networks · Computer Science 2020-11-13 Zhenghao Zhang , Jianbin Huang , Qinglin Tan

We construct a structure-preserving finite element method and time-stepping scheme for inhomogeneous, incompressible magnetohydrodynamics (MHD). The method preserves energy, cross-helicity (when the fluid density is constant), magnetic…

Numerical Analysis · Mathematics 2020-12-09 Evan S. Gawlik , François Gay-Balmaz

We describe a novel splitting approach to numerical relativistic magnetohydrodynamics (RMHD) designed to expand its applicability to the domain of ultra-high magnetisation (high-$\sigma$). In this approach, the electromagnetic field is…

High Energy Astrophysical Phenomena · Physics 2024-11-18 Serguei Komissarov , David Phillips

This paper considers magnetohydrodynamics (MHD) and some of its applications from the perspective of differential geometry, considering the dynamics of an ideal fluid flow and magnetic field on a general three-dimensional manifold, equipped…

Fluid Dynamics · Physics 2023-07-26 Andrew D. Gilbert , Jacques Vanneste

This article introduces a new 3D magnetohydrodynamic (MHD) equilibrium solver, based on the concept of admissible variations of B, p that allows for magnetic relaxation of a magnetic field in a perturbed/non-minimum energy state to a lower…

Computational Physics · Physics 2025-11-03 Tobias Blickhan , Julianne Stratton , Alan A. Kaptanoglu

The robotic systems continuously interact with complex dynamical systems in the physical world. Reliable predictions of spatiotemporal evolution of these dynamical systems, with limited knowledge of system dynamics, are crucial for…

Artificial Intelligence · Computer Science 2019-01-08 Yun Long , Xueyuan She , Saibal Mukhopadhyay

In magnetic confinement fusion research, the achievement of high plasma pressure is key to reaching the goal of net energy production. The magnetohydrodynamic (MHD) model is used to self-consistently calculate the effects the plasma…

The relativistic magnetohydrodynamics (RMHD) set of equations has recently seen increased use in astrophysical computations. Even so, RMHD codes remain fragile. The reconstruction can sometimes yield superluminal velocities in certain parts…

High Energy Astrophysical Phenomena · Physics 2016-03-23 Dinshaw S. Balsara , Jinho Kim

High-accuracy, high-efficiency physics-based fluid-solid interaction is essential for reality modeling and computer animation in online games or real-time Virtual Reality (VR) systems. However, the large-scale simulation of incompressible…

Graphics · Computer Science 2023-05-08 Jin Li , Yang Gao , Ju Dai , Shuai Li , Aimin Hao , Hong Qin

After finding the really self-consistent electromagnetic equations for a plasma, we proceed in a similar fashion to find how the MHD equations have to be modified accordingly. Substantially this is done by replacing the "Lorentz" force…

Mathematical Physics · Physics 2007-05-23 Evangelos Chaliasos

In this note we consider the ideal compressible magneto-hydrodynamics (MHD) equations in a special two dimensional setting. We show that there exist particular initial data for which one obtains infinitely many entropy-conserving weak…

Analysis of PDEs · Mathematics 2021-02-04 Christian Klingenberg , Simon Markfelder

Magneto-hydrodynamics is one of the foremost models in plasma physics with applications in inertial confinement fusion, astrophysics and elsewhere. Advanced numerical methods are needed to get an insight into the complex physical phenomena.…

Computational Physics · Physics 2022-03-29 Jan Nikl , Milan Kuchařík , Stefan Weber

In this paper we show how the Smoothed Particle Hydrodynamics (SPH) equations for ideal magnetohydrodynamics (MHD) can be written in conservation form with the positivity of the dissipation guaranteed. We call the resulting algorithm…

Astrophysics · Physics 2016-08-30 D. J. Price , J. J. Monaghan

The paper describes a new upwind conservative numerical scheme for special relativistic resistive magnetohydrodynamics with scalar resistivity. The magnetic field is kept approximately divergence free and the divergence of the electric…

Astrophysics · Physics 2009-11-13 S. S. Komissarov

This work presents structure-preserving Lift & Learn, a scientific machine learning method that employs lifting variable transformations to learn structure-preserving reduced-order models for nonlinear partial differential equations (PDEs)…

Machine Learning · Computer Science 2026-01-09 Harsh Sharma , Juan Diego Draxl Giannoni , Boris Kramer